30 posts
Anthropic published the production playbook for MCP: 300M SDK downloads, thin tools over 2,500 endpoints, OAuth vaults. The playbook stops at the tool call. Argument-level policy is what comes next.
Cloudflare's enterprise MCP launch solves discovery, access, and shadow-MCP prevention. That's the baseline. The harder question — what agents are allowed to do once they're inside — needs a different primitive.
Microsoft open-sourced a nine-package agent governance toolkit. It validates the space — but it doesn't address MCP. Here's what that means for teams running MCP agents in production.
A 10-point checklist for deploying AI agents that call APIs, move money, and modify databases. Covers deny-by-default, spend limits, rate limiting, and approval workflows.
MCP policy enforcement intercepts every AI agent tool call and evaluates it against deterministic rules before execution. Here's how it works and how to set it up.
System prompts can't enforce spending limits or prevent destructive operations. Here's why prompt guardrails fail for tool-calling AI agents and what works instead.
Bain & Company's agentic AI architecture framework calls for centralised policy enforcement across MCP tool calls. Intercept is the open-source implementation.
X released an official MCP server with 131 tools — including posting, DMs, follows, and deletes. Here's why that's a problem and how to enforce policies on it.
MPP lets agents spend money autonomously. Intercept is the first MCP proxy that reads the actual price from the server and enforces YAML-defined budgets before any payment leaves the wallet.
Cloudflare, Stripe, Supabase, Sentry, Firebase — we ran PolicyLayer's scan against real .mcp.json files from well-known repos. Most expose destructive tools with zero policy enforcement.
Most teams will wrap their own dangerous tools. The real market for agent control only gets large if agents become dynamic consumers of external services the team did not fully pre-wrap.
Security researchers filed 30+ CVEs against MCP servers in early 2026. Patching individual servers doesn't fix the structural gap. The real fix is a policy layer that works across all of them.
A new research paper argues that LLMs cannot self-enforce security constraints. Intercept implements every recommendation — as open-source software you can deploy today.
The AWS MCP server exposes 55 tools for EC2, S3, Lambda, and RDS. Here's how to block destructive operations and rate limit resource creation.
The Cloudflare MCP server gives AI agents access to DNS changes, worker deployments, and zone management. Here's how to block deletions and rate limit infrastructure changes.
The Docker MCP server gives AI agents access to container removal, image deletion, and volume destruction. Here's how to block destructive operations.
The filesystem MCP server gives AI agents unrestricted read and write access. Here's how to rate limit file operations and prevent destructive mistakes.
The GitHub MCP server exposes 83 tools — including file deletion, repo creation, and PR merges. Here's how to enforce policies before your agent ships something it shouldn't.
The Gmail MCP server gives AI agents access to send emails, delete messages in bulk, and manage your inbox. Here's how to rate limit sends and block batch operations.
The PostgreSQL MCP server exposes a raw SQL query tool with no restrictions. Here's how to rate limit queries before your agent drops a table.
The Redis MCP server lets AI agents run SET, DELETE, and FLUSHALL. Here's how to block destructive commands and rate limit writes.
The Slack MCP server lets AI agents post messages, reply to threads, and add reactions. Here's how to rate limit messaging before your agent spams your workspace.
The Stripe MCP server exposes 27 tools to AI agents — refunds, charges, payment links. Add rate limits and spending caps before something goes wrong.
LLMs can't reliably self-enforce safety rules. Deterministic policy enforcement outside the model catches what prompts miss — here's the architecture.
What happens when your AI agent goes rogue? Six failure modes — runaway loops, spending spirals, destructive ops — and the deterministic policies that stop them.
Prompt guardrails for MCP agents are bypassable and unauditable. Why deterministic policy enforcement at the transport layer is the real security primitive.
Add per-tool and global rate limits to any MCP server in under 5 minutes. Copy-paste YAML policies for counters, wildcards, and stateful tracking.
A step-by-step guide to adding transaction limits, daily spend caps, and currency restrictions to MCP-connected AI agents using YAML policies and the Intercept proxy.
npx @policylayer/mcp init takes you from zero to policy-enforced AI agent in under a minute. Browser auth, guided setup, and MCP tools your agent discovers automatically.
MCP servers are giving AI agents access to wallets, bridges, and DeFi. Here's how to enforce spending limits on any MCP-powered agent in under five minutes.